Zero-inflated binary tree Pólya-splitting distrubtions for joint species distribution models

Understanding the impact of climate change on tropical rainforest ecosystems is crucial to promote efficient conservation strategies. The classical approach remains the use of species-specific distribution model. However, in species-rich ecosystems with many rare species, such an approach is doomed to failure. Moreover, univariate approaches ignore species dependencies. However, biodiversity is not merely the sum of species but the result of multiple interactions. Modeling multivariate count data allowing for flexible dependencies as well as zero inflation and overdispersion is challenging. In this presentation, we develop a new family of models called the zero-inflated binary tree Pólya-splitting models. This family allows the decomposition of a multivariate count data into a successive sub-model along a known binary partition tree. Model is illustrated on a real case study based on an impressive dataset consisting of the abundance of more than 180 tree taxa sampled on 1,571 plots covering more than 6 million hectares from the Congo Basin tropical rainforests.